DDT: a research tool for automatic data distribution in HPF

This article describes the main features and implementation of our automatic data distribution research tool. The tool (DDT) accepts programs written in Fortran 77 and generates High Performance Fortran (HPF) directives to map arrays onto the memories of the processors and parallelize loops, and executable statements to remap these arrays. DDT works by identifying a set of computational phases (procedures and loops). The algorithm builds a search space of candidate solutions for these phases which is explored looking for the combination that minimizes the overall cost; this cost includes data movement cost and computation cost. The movement cost reflects the cost of accessing remote data during the execution of a phase and the remapping costs that have to be paid in order to execute the phase with the selected mapping. The computation cost includes the cost of executing a phase in parallel according to the selected mapping and the owner computes rule. The tool supports interprocedural analysis and uses control flow information to identify how phases are sequenced during the execution of the application.Peer ReviewedPostprint (published version

Automatic Data and Computation Mapping for Distributed-Memory Machines.

Distributed memory parallel computers offer enormous computation power, scalability and flexibility. However, these machines are difficult to program and this limits their widespread use. An important characteristic of these machines is the difference in the access time for data in local versus non-local memory; non-local memory accesses are much slower than local memory accesses. This is also a characteristic of shared memory machines but to a less degree. Therefore it is essential that as far as possible, the data that needs to be accessed by a processor during the execution of the computation assigned to it reside in its local memory rather than in some other processor\u27s memory. Several research projects have concluded that proper mapping of data is key to realizing the performance potential of distributed memory machines. Current language design efforts such as Fortran D and High Performance Fortran (HPF) are based on this. It is our thesis that for many practical codes, it is possible to derive good mappings through a combination of algorithms and systematic procedures. We view mapping as consisting of wo phases, alignment followed by distribution. For the alignment phase we present three constraint-based methods--one based on a linear programming formulation of the problem; the second formulates the alignment problem as a constrained optimization problem using Lagrange multipliers; the third method uses a heuristic to decide which constraints to leave unsatisfied (based on the penalty of increased communication incurred in doing so) in order to find a mapping. In addressing the distribution phase, we have developed two methods that integrate the placement of computation--loop nests in our case--with the mapping of data. For one distributed dimension, our approach finds the best combination of data and computation mapping that results in low communication overhead; this is done by choosing a loop order that allows message vectorization. In the second method, we introduce the distribution preference graph and the operations on this graph allow us to integrate loop restructuring transformations and data mapping. These techniques produce mappings that have been used in efficient hand-coded implementations of several benchmark codes

Directions in parallel programming: HPF, shared virtual memory and object parallelism in pC++

Fortran and C++ are the dominant programming languages used in scientific computation. Consequently, extensions to these languages are the most popular for programming massively parallel computers. We discuss two such approaches to parallel Fortran and one approach to C++. The High Performance Fortran Forum has designed HPF with the intent of supporting data parallelism on Fortran 90 applications. HPF works by asking the user to help the compiler distribute and align the data structures with the distributed memory modules in the system. Fortran-S takes a different approach in which the data distribution is managed by the operating system and the user provides annotations to indicate parallel control regions. In the case of C++, we look at pC++ which is based on a concurrent aggregate parallel model

Activities of the Research Institute for Advanced Computer Science

The Research Institute for Advanced Computer Science (RIACS) was established by the Universities Space Research Association (USRA) at the NASA Ames Research Center (ARC) on June 6, 1983. RIACS is privately operated by USRA, a consortium of universities with research programs in the aerospace sciences, under contract with NASA. The primary mission of RIACS is to provide research and expertise in computer science and scientific computing to support the scientific missions of NASA ARC. The research carried out at RIACS must change its emphasis from year to year in response to NASA ARC's changing needs and technological opportunities. Research at RIACS is currently being done in the following areas: (1) parallel computing; (2) advanced methods for scientific computing; (3) high performance networks; and (4) learning systems. RIACS technical reports are usually preprints of manuscripts that have been submitted to research journals or conference proceedings. A list of these reports for the period January 1, 1994 through December 31, 1994 is in the Reports and Abstracts section of this report

NASA high performance computing and communications program

The National Aeronautics and Space Administration's HPCC program is part of a new Presidential initiative aimed at producing a 1000-fold increase in supercomputing speed and a 100-fold improvement in available communications capability by 1997. As more advanced technologies are developed under the HPCC program, they will be used to solve NASA's 'Grand Challenge' problems, which include improving the design and simulation of advanced aerospace vehicles, allowing people at remote locations to communicate more effectively and share information, increasing scientist's abilities to model the Earth's climate and forecast global environmental trends, and improving the development of advanced spacecraft. NASA's HPCC program is organized into three projects which are unique to the agency's mission: the Computational Aerosciences (CAS) project, the Earth and Space Sciences (ESS) project, and the Remote Exploration and Experimentation (REE) project. An additional project, the Basic Research and Human Resources (BRHR) project exists to promote long term research in computer science and engineering and to increase the pool of trained personnel in a variety of scientific disciplines. This document presents an overview of the objectives and organization of these projects as well as summaries of individual research and development programs within each project

Alk1 Signaling in Vascular Development

Heterozygous loss of the endothelial-specific transforming growth factor-beta (TGF-β) Type 1 receptor, activin receptor-like kinase 1 (ALK1), results in the autosomal dominant disorder, hereditary hemorrhagic telangiectasia type 2 (HHT2), which is characterized by mucocutaneous telangiectasias as well as arteriovenous malformations (AVMs) in the brain, lungs, liver, gastrointestinal tract, and spinal cord. As a result, patients suffer from a range of clinical symptoms including epistaxis, hemorrhage, and stroke. Using zebrafish, our laboratory has demonstrated that AVMs form via a two-step mechanism involving an initial increase in endothelial cell number caused by lack of alk1, and then an adaptive response to increased blood flow in downstream vessels. This adaptive response involves increased arterial caliber and maintenance of normally transient connections between arteries and veins, thereby forming high-flow AVMs. Furthermore, we have demonstrated that alk1 expression is dependent on blood flow, and that lack of flow mimics loss of alk1, suggesting that Alk1 might act downstream of blood flow to stabilize arterial caliber. To date, the in vivo ligand and intracellular mediators required for flow-dependent, Alk1-mediated endothelial quiescence and AVM prevention remain unknown. In this work, I demonstrate that bone morphogenetic protein 10 (Bmp10) is the physiologically relevant Alk1 ligand during zebrafish embryonic development. Bmp10 paralogs are expressed exclusively in the heart, and loss of blood flow affects arterial pSmad1/5/9, cxcr4a, and edn1 expression similarly to loss of alk1, even when alk1 expression is restored via a flow-independent transgene. Together, these data suggest that flow is required not only for alk1 expression but also to deliver cardiac-derived Bmp10 ligand to arterial endothelial cell Alk1 to promote endothelial cell quiescence. Downstream of Bmp10/Alk1, Alk1 kinase activity is required to prevent AVMs. However characterization of a pSmad1/5-responsive transgenic reporter, Tg(BRE:EGFP), suggests that although phosphorylation of Smad1/5/9 in arterial endothelium is clearly dependent on Alk1, pSmad1/5/9 may not activate transcription via a canonical mechanism within these cells. In sum, the work presented in this thesis constructs a novel blood flow-responsive signaling pathway, suggests novel mechanisms by which Alk1 may control gene expression, and finally, describes a new tool for studying Alk1 and BMP signaling in vivo

Complete 2018 Program

Program and schedule of events for the 29th Annual John Wesley Powell Student Research Conference